[XPU] Upgrade torch 2.11 for xpu (#37947)

Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>

docker/Dockerfile.xpu

@@ -50,9 +50,9 @@ RUN curl -LsSf https://astral.sh/uv/install.sh | sh
 RUN uv venv --python ${PYTHON_VERSION} --seed ${VIRTUAL_ENV}
 ENV PATH="$VIRTUAL_ENV/bin:$PATH"
 
-# This oneccl contains the BMG support which is not the case for default version of oneapi 2025.2.
-ARG ONECCL_INSTALLER="intel-oneccl-2021.15.7.8_offline.sh"
-RUN wget "https://github.com/uxlfoundation/oneCCL/releases/download/2021.15.7/${ONECCL_INSTALLER}" && \
+# This oneccl contains the BMG support which is not the case for default version of oneapi 2025.3.
+ARG ONECCL_INSTALLER="intel-oneccl-2021.15.9.14_offline.sh"
+RUN wget "https://github.com/uxlfoundation/oneCCL/releases/download/2021.15.9/${ONECCL_INSTALLER}" && \
     bash "${ONECCL_INSTALLER}" -a --silent --eula accept && \
     rm "${ONECCL_INSTALLER}" && \
     echo "source /opt/intel/oneapi/setvars.sh --force" >> /root/.bashrc && \
@@ -164,7 +164,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
 # FIX triton
 RUN --mount=type=cache,target=/root/.cache/uv \
     uv pip uninstall triton triton-xpu && \
-    uv pip install triton-xpu==3.6.0
+    uv pip install triton-xpu==3.7.0
 
 # remove torch bundled oneccl to avoid conflicts
 RUN --mount=type=cache,target=/root/.cache/uv \

docs/getting_started/installation/gpu.xpu.inc.md

@@ -46,7 +46,7 @@ pip install -v -r requirements/xpu.txt
 
     !!! note
         - `triton` (without suffix) is for NVIDIA GPUs only. On XPU, using it instead of `triton-xpu` can cause correctness or runtime issues.
-        - For torch 2.10 (the version used in `requirements/xpu.txt`), the matching package is `triton-xpu==3.6.0`. If you use a different version of torch, check the corresponding `triton-xpu` version in [docker/Dockerfile.xpu](https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile.xpu).
+        - For torch 2.11 (the version used in `requirements/xpu.txt`), the matching package is `triton-xpu==3.7.0`. If you use a different version of torch, check the corresponding `triton-xpu` version in [docker/Dockerfile.xpu](https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile.xpu).
 
 - Finally, build and install vLLM XPU backend:
 

requirements/test/xpu.txt

@@ -93,7 +93,7 @@ docker==7.1.0
     # via gpt-oss
 docopt==0.6.2
     # via num2words
-dpcpp-cpp-rt==2025.3.1
+dpcpp-cpp-rt==2025.3.2
     # via
     #   onemkl-sycl-blas
     #   onemkl-sycl-dft
@@ -172,27 +172,27 @@ idna==3.11
     #   yarl
 imageio==2.37.3
     # via scikit-image
-impi-rt==2021.17.0
+impi-rt==2021.17.2
     # via
     #   oneccl
     #   torch
 iniconfig==2.3.0
     # via pytest
-intel-cmplr-lib-rt==2025.3.1
+intel-cmplr-lib-rt==2025.3.2
     # via
     #   intel-sycl-rt
     #   torch
-intel-cmplr-lib-ur==2025.3.1
+intel-cmplr-lib-ur==2025.3.2
     # via
     #   intel-openmp
     #   intel-sycl-rt
     #   torch
-intel-cmplr-lic-rt==2025.3.1
+intel-cmplr-lic-rt==2025.3.2
     # via
     #   intel-opencl-rt
     #   intel-sycl-rt
     #   torch
-intel-opencl-rt==2025.3.1
+intel-opencl-rt==2025.3.2
     # via
     #   dpcpp-cpp-rt
     #   onemkl-sycl-blas
@@ -201,14 +201,14 @@ intel-opencl-rt==2025.3.1
     #   onemkl-sycl-rng
     #   onemkl-sycl-sparse
     #   torch
-intel-openmp==2025.3.1
+intel-openmp==2025.3.2
     # via
     #   dpcpp-cpp-rt
     #   mkl
     #   torch
-intel-pti==0.15.0
+intel-pti==0.16.0
     # via torch
-intel-sycl-rt==2025.3.1
+intel-sycl-rt==2025.3.2
     # via
     #   dpcpp-cpp-rt
     #   oneccl
@@ -270,7 +270,7 @@ mistral-common==1.11.0
     # via
     #   -c requirements/common.txt
     #   -r requirements/test/xpu.in
-mkl==2025.3.0
+mkl==2025.3.1
     # via
     #   onemkl-sycl-blas
     #   onemkl-sycl-dft
@@ -335,28 +335,28 @@ numpy==2.2.6
     #   tifffile
     #   torchvision
     #   transformers
-oneccl==2021.17.1
+oneccl==2021.17.2
     # via
     #   oneccl-devel
     #   torch
-oneccl-devel==2021.17.1
+oneccl-devel==2021.17.2
     # via torch
-onemkl-license==2025.3.0
+onemkl-license==2025.3.1
     # via
     #   mkl
     #   torch
-onemkl-sycl-blas==2025.3.0
+onemkl-sycl-blas==2025.3.1
     # via
     #   onemkl-sycl-lapack
     #   onemkl-sycl-sparse
     #   torch
-onemkl-sycl-dft==2025.3.0
+onemkl-sycl-dft==2025.3.1
     # via torch
-onemkl-sycl-lapack==2025.3.0
+onemkl-sycl-lapack==2025.3.1
     # via torch
-onemkl-sycl-rng==2025.3.0
+onemkl-sycl-rng==2025.3.1
     # via torch
-onemkl-sycl-sparse==2025.3.0
+onemkl-sycl-sparse==2025.3.1
     # via torch
 openai-harmony==0.0.8
     # via
@@ -608,7 +608,7 @@ tabledata==1.3.4
     # via pytablewriter
 tabulate==0.10.0
     # via sacrebleu
-tbb==2022.3.0
+tbb==2022.3.1
     # via
     #   intel-opencl-rt
     #   mkl
@@ -645,7 +645,7 @@ tokenizers==0.22.2
     # via
     #   -c requirements/common.txt
     #   transformers
-torch==2.10.0+xpu
+torch==2.11.0+xpu
     # via
     #   -c requirements/xpu.txt
     #   accelerate
@@ -653,7 +653,7 @@ torch==2.10.0+xpu
     #   sentence-transformers
     #   timm
     #   torchvision
-torchvision==0.25.0+xpu
+torchvision==0.26.0+xpu
     # via timm
 tqdm==4.67.3
     # via
@@ -671,7 +671,7 @@ transformers==5.5.3
     # via
     #   -c requirements/common.txt
     #   sentence-transformers
-triton-xpu==3.6.0
+triton-xpu==3.7.0
     # via torch
 typepy==1.3.4
     # via
@@ -710,7 +710,7 @@ typing-inspection==0.4.2
     # via
     #   fastapi
     #   pydantic
-umf==1.0.2
+umf==1.0.3
     # via
     #   intel-cmplr-lib-ur
     #   torch

requirements/xpu.txt

@@ -11,7 +11,7 @@ jinja2>=3.1.6
 datasets # for benchmark scripts
 numba == 0.61.2 # Required for N-gram speculative decoding
 --extra-index-url=https://download.pytorch.org/whl/xpu
-torch==2.10.0+xpu
+torch==2.11.0+xpu
 torchaudio
 torchvision